Overview

Dataset statistics

Number of variables13
Number of observations235
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory24.0 KiB
Average record size in memory104.5 B

Variable types

NUM13

Reproduction

Analysis started2020-08-25 00:59:18.370053
Analysis finished2020-08-25 00:59:41.849715
Duration23.48 seconds
Versionpandas-profiling v2.8.0
Command linepandas_profiling --config_file config.yaml [YOUR_FILE.csv]
Download configurationconfig.yaml

Warnings

col_3 is highly correlated with col_2 and 1 other fieldsHigh correlation
col_2 is highly correlated with col_3High correlation
col_4 is highly correlated with col_3High correlation
col_6 is highly correlated with col_5 and 2 other fieldsHigh correlation
col_5 is highly correlated with col_6 and 1 other fieldsHigh correlation
col_7 is highly correlated with col_6 and 2 other fieldsHigh correlation
col_8 is highly correlated with col_5 and 3 other fieldsHigh correlation
col_9 is highly correlated with col_7 and 2 other fieldsHigh correlation
col_10 is highly correlated with col_9 and 2 other fieldsHigh correlation
col_11 is highly correlated with col_10 and 2 other fieldsHigh correlation
col_12 is highly correlated with col_10 and 2 other fieldsHigh correlation
target is highly correlated with col_11 and 1 other fieldsHigh correlation
col_1 has unique values Unique
col_2 has 8 (3.4%) zeros Zeros
col_3 has 6 (2.6%) zeros Zeros
col_4 has 5 (2.1%) zeros Zeros
col_5 has 7 (3.0%) zeros Zeros
col_6 has 7 (3.0%) zeros Zeros
col_7 has 7 (3.0%) zeros Zeros
col_8 has 3 (1.3%) zeros Zeros
col_9 has 5 (2.1%) zeros Zeros
col_10 has 5 (2.1%) zeros Zeros
col_11 has 3 (1.3%) zeros Zeros
col_12 has 5 (2.1%) zeros Zeros
target has 6 (2.6%) zeros Zeros

Variables

col_1
Real number (ℝ≥0)

UNIQUE

Distinct count235
Unique (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1866.0
Minimum1749.0
Maximum1983.0
Zeros0
Zeros (%)0.0%
Memory size2.0 KiB
2020-08-25T00:59:41.892879image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/

Quantile statistics

Minimum1749
5-th percentile1760.7
Q11807.5
median1866
Q31924.5
95-th percentile1971.3
Maximum1983
Range234
Interquartile range (IQR)117

Descriptive statistics

Standard deviation67.98284097
Coefficient of variation (CV)0.03643239066
Kurtosis-1.2
Mean1866
Median Absolute Deviation (MAD)59
Skewness0
Sum438510
Variance4621.666667
2020-08-25T00:59:41.986544image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%) 
197310.4%
 
189810.4%
 
185810.4%
 
183810.4%
 
185310.4%
 
183410.4%
 
181410.4%
 
180710.4%
 
193810.4%
 
193410.4%
 
188510.4%
 
193010.4%
 
192610.4%
 
178310.4%
 
187010.4%
 
183310.4%
 
193710.4%
 
184210.4%
 
177410.4%
 
176710.4%
 
182610.4%
 
178210.4%
 
175310.4%
 
175410.4%
 
197910.4%
 
Other values (210)21089.4%
 
ValueCountFrequency (%) 
174910.4%
 
175010.4%
 
175110.4%
 
175210.4%
 
175310.4%
 
175410.4%
 
175510.4%
 
175610.4%
 
175710.4%
 
175810.4%
 
ValueCountFrequency (%) 
198310.4%
 
198210.4%
 
198110.4%
 
198010.4%
 
197910.4%
 
197810.4%
 
197710.4%
 
197610.4%
 
197510.4%
 
197410.4%
 

col_2
Real number (ℝ≥0)

HIGH CORRELATION
ZEROS

Distinct count203
Unique (%)86.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean49.111914900389124
Minimum0.0
Maximum217.3999938964844
Zeros8
Zeros (%)3.4%
Memory size2.0 KiB
2020-08-25T00:59:42.091873image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0.5
Q114.60000038
median40.59999847
Q370
95-th percentile135.6899979
Maximum217.3999939
Range217.3999939
Interquartile range (IQR)55.39999962

Descriptive statistics

Standard deviation42.89731861
Coefficient of variation (CV)0.8734605175
Kurtosis1.690859988
Mean49.1119149
Median Absolute Deviation (MAD)27.09999847
Skewness1.277374742
Sum11541.3
Variance1840.179944
2020-08-25T00:59:42.191949image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%) 
083.4%
 
7031.3%
 
2431.3%
 
4531.3%
 
0.800000011920.9%
 
12.3000001920.9%
 
36.4000015320.9%
 
48.2999992420.9%
 
45.2999992420.9%
 
18.8999996220.9%
 
31.6000003820.9%
 
3.40000009520.9%
 
38.7000007620.9%
 
9.39999961920.9%
 
11.3000001920.9%
 
14.6000003820.9%
 
0.20000000320.9%
 
0.520.9%
 
3920.9%
 
11420.9%
 
1220.9%
 
19.2000007620.9%
 
5820.9%
 
8.10000038110.4%
 
62.5999984710.4%
 
Other values (178)17875.7%
 
ValueCountFrequency (%) 
083.4%
 
0.20000000320.9%
 
0.300000011910.4%
 
0.520.9%
 
0.800000011920.9%
 
1.60000002410.4%
 
210.4%
 
2.29999995210.4%
 
2.79999995210.4%
 
3.29999995210.4%
 
ValueCountFrequency (%) 
217.399993910.4%
 
202.510.4%
 
18810.4%
 
177.300003110.4%
 
166.600006110.4%
 
16510.4%
 
159.600006110.4%
 
159.100006110.4%
 
156.699996910.4%
 
146.300003110.4%
 

col_3
Real number (ℝ≥0)

HIGH CORRELATION
ZEROS

Distinct count211
Unique (%)89.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean51.17489381622761
Minimum0.0
Maximum182.3000030517578
Zeros6
Zeros (%)2.6%
Memory size2.0 KiB
2020-08-25T00:59:42.296702image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1.319999993
Q115.6500001
median44
Q374.5
95-th percentile129.4999969
Maximum182.3000031
Range182.3000031
Interquartile range (IQR)58.8499999

Descriptive statistics

Standard deviation41.85909544
Coefficient of variation (CV)0.8179615495
Kurtosis0.1615872448
Mean51.17489382
Median Absolute Deviation (MAD)29.10000038
Skewness0.8827122132
Sum12026.10005
Variance1752.183871
2020-08-25T00:59:42.401581image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%) 
062.6%
 
22.2000007631.3%
 
64.1999969520.9%
 
93.5999984720.9%
 
42.9000015320.9%
 
4.30000019120.9%
 
24.3999996220.9%
 
820.9%
 
0.600000023820.9%
 
24.520.9%
 
2920.9%
 
10620.9%
 
7.09999990520.9%
 
2620.9%
 
5120.9%
 
4420.9%
 
125.300003120.9%
 
0.520.9%
 
9.19999980920.9%
 
86.9000015310.4%
 
14.8999996210.4%
 
4.19999980910.4%
 
47.5999984710.4%
 
44.0999984710.4%
 
50.0999984710.4%
 
Other values (186)18679.1%
 
ValueCountFrequency (%) 
062.6%
 
0.520.9%
 
0.600000023820.9%
 
0.699999988110.4%
 
0.899999976210.4%
 
1.510.4%
 
1.89999997610.4%
 
2.40000009510.4%
 
2.59999990510.4%
 
2.90000009510.4%
 
ValueCountFrequency (%) 
182.300003110.4%
 
175.600006110.4%
 
165.699996910.4%
 
164.899993910.4%
 
163.600006110.4%
 
15510.4%
 
143.100006110.4%
 
142.510.4%
 
141.300003110.4%
 
137.510.4%
 

col_4
Real number (ℝ≥0)

HIGH CORRELATION
ZEROS

Distinct count209
Unique (%)88.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean50.04085110184994
Minimum0.0
Maximum190.6999969482422
Zeros5
Zeros (%)2.1%
Memory size2.0 KiB
2020-08-25T00:59:42.516042image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1.869999969
Q114.79999971
median45.59999847
Q372.25
95-th percentile134.8700043
Maximum190.6999969
Range190.6999969
Interquartile range (IQR)57.45000029

Descriptive statistics

Standard deviation40.68973213
Coefficient of variation (CV)0.8131302972
Kurtosis0.5884392152
Mean50.0408511
Median Absolute Deviation (MAD)29.09999847
Skewness0.9534677883
Sum11759.60001
Variance1655.654301
2020-08-25T00:59:42.622375image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%) 
052.1%
 
7.80000019131.3%
 
45.7000007620.9%
 
21.7000007620.9%
 
26.2000007620.9%
 
3020.9%
 
5.69999980920.9%
 
66.520.9%
 
55.520.9%
 
4.520.9%
 
12.3999996220.9%
 
26.7000007620.9%
 
1120.9%
 
5320.9%
 
60.7000007620.9%
 
4.90000009520.9%
 
64.5999984720.9%
 
94.8000030520.9%
 
46.4000015320.9%
 
66.3000030520.9%
 
11.6999998120.9%
 
80.0999984720.9%
 
13.8999996210.4%
 
29.7000007610.4%
 
77.6999969510.4%
 
Other values (184)18478.3%
 
ValueCountFrequency (%) 
052.1%
 
0.40000000610.4%
 
0.510.4%
 
0.600000023810.4%
 
0.699999988110.4%
 
0.899999976210.4%
 
1.70000004810.4%
 
1.79999995210.4%
 
1.89999997610.4%
 
3.09999990510.4%
 
ValueCountFrequency (%) 
190.699996910.4%
 
185.699996910.4%
 
159.399993910.4%
 
157.510.4%
 
157.399993910.4%
 
153.800003110.4%
 
143.300003110.4%
 
143.199996910.4%
 
140.800003110.4%
 
13810.4%
 

col_5
Real number (ℝ≥0)

HIGH CORRELATION
ZEROS

Distinct count202
Unique (%)86.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean51.002978531509
Minimum0.0
Maximum196.0
Zeros7
Zeros (%)3.0%
Memory size2.0 KiB
2020-08-25T00:59:42.740933image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1.54000001
Q116.55000019
median41
Q375.29999924
95-th percentile143.5299957
Maximum196
Range196
Interquartile range (IQR)58.74999905

Descriptive statistics

Standard deviation42.73194942
Coefficient of variation (CV)0.8378324295
Kurtosis0.7105406595
Mean51.00297853
Median Absolute Deviation (MAD)28.19999695
Skewness1.051428376
Sum11985.69995
Variance1826.019501
2020-08-25T00:59:42.849535image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%) 
073.0%
 
5.09999990531.3%
 
32.9000015331.3%
 
11.3000001931.3%
 
3120.9%
 
12220.9%
 
71.8000030520.9%
 
3220.9%
 
11.1999998120.9%
 
29.1000003820.9%
 
31.7000007620.9%
 
23.7999992420.9%
 
8.39999961920.9%
 
75.6999969520.9%
 
26.3999996220.9%
 
26.1000003820.9%
 
4120.9%
 
9520.9%
 
6.520.9%
 
14520.9%
 
60.7000007620.9%
 
26.8999996220.9%
 
43.7999992420.9%
 
19.3999996220.9%
 
107.099998520.9%
 
Other values (177)17775.3%
 
ValueCountFrequency (%) 
073.0%
 
0.100000001510.4%
 
0.300000011910.4%
 
0.899999976210.4%
 
1.10000002410.4%
 
1.39999997610.4%
 
1.60000002410.4%
 
1.79999995210.4%
 
2.29999995210.4%
 
2.510.4%
 
ValueCountFrequency (%) 
19610.4%
 
189.699996910.4%
 
175.199996910.4%
 
164.100006110.4%
 
163.300003110.4%
 
162.399993910.4%
 
16010.4%
 
156.399993910.4%
 
149.800003110.4%
 
14710.4%
 

col_6
Real number (ℝ≥0)

HIGH CORRELATION
ZEROS

Distinct count207
Unique (%)88.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean52.47829770864325
Minimum0.0
Maximum238.8999938964844
Zeros7
Zeros (%)3.0%
Memory size2.0 KiB
2020-08-25T00:59:43.134062image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile2.280000067
Q119.65000057
median41.29999924
Q376.79999924
95-th percentile136.9000061
Maximum238.8999939
Range238.8999939
Interquartile range (IQR)57.14999866

Descriptive statistics

Standard deviation45.08715565
Coefficient of variation (CV)0.8591581209
Kurtosis1.33575209
Mean52.47829771
Median Absolute Deviation (MAD)28.39999962
Skewness1.188245749
Sum12332.39996
Variance2032.851605
2020-08-25T00:59:43.233345image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%) 
073.0%
 
44.2999992431.3%
 
920.9%
 
39.520.9%
 
107.199996920.9%
 
12.8999996220.9%
 
67.520.9%
 
21.2000007620.9%
 
5.80000019120.9%
 
127.520.9%
 
41.0999984720.9%
 
2020.9%
 
38.0999984720.9%
 
2.40000009520.9%
 
22.2000007620.9%
 
3.20000004820.9%
 
20.7000007620.9%
 
106.199996920.9%
 
53.7999992420.9%
 
3620.9%
 
12.520.9%
 
2.79999995220.9%
 
57.510.4%
 
15.3999996210.4%
 
2510.4%
 
Other values (182)18277.4%
 
ValueCountFrequency (%) 
073.0%
 
0.800000011910.4%
 
110.4%
 
1.510.4%
 
1.70000004810.4%
 
210.4%
 
2.40000009520.9%
 
2.510.4%
 
2.79999995220.9%
 
2.90000009510.4%
 
ValueCountFrequency (%) 
238.899993910.4%
 
201.300003110.4%
 
179.899993910.4%
 
17610.4%
 
175.300003110.4%
 
17410.4%
 
17210.4%
 
164.600006110.4%
 
152.699996910.4%
 
145.510.4%
 

col_7
Real number (ℝ≥0)

HIGH CORRELATION
ZEROS

Distinct count205
Unique (%)87.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean51.54936172385165
Minimum0.0
Maximum200.6999969482422
Zeros7
Zeros (%)3.0%
Memory size2.0 KiB
2020-08-25T00:59:43.341414image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1.469999993
Q115.54999971
median40.5
Q380.94999695
95-th percentile126.3799988
Maximum200.6999969
Range200.6999969
Interquartile range (IQR)65.39999723

Descriptive statistics

Standard deviation42.51301897
Coefficient of variation (CV)0.8247050506
Kurtosis0.4801739821
Mean51.54936172
Median Absolute Deviation (MAD)29.10000038
Skewness0.9551033566
Sum12114.10001
Variance1807.356782
2020-08-25T00:59:43.451189image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%) 
073.0%
 
11.3999996231.3%
 
77.4000015320.9%
 
63.2000007620.9%
 
7020.9%
 
520.9%
 
36.4000015320.9%
 
4020.9%
 
12.3000001920.9%
 
31.7000007620.9%
 
3620.9%
 
26.7000007620.9%
 
1.29999995220.9%
 
20.520.9%
 
48.2999992420.9%
 
5.80000019120.9%
 
65.0999984720.9%
 
31.1000003820.9%
 
6.69999980920.9%
 
6.40000009520.9%
 
9.10000038120.9%
 
8820.9%
 
73.520.9%
 
4920.9%
 
55.9000015310.4%
 
Other values (180)18076.6%
 
ValueCountFrequency (%) 
073.0%
 
0.20000000310.4%
 
110.4%
 
1.29999995220.9%
 
1.39999997610.4%
 
1.510.4%
 
1.60000002410.4%
 
1.79999995210.4%
 
2.20000004810.4%
 
310.4%
 
ValueCountFrequency (%) 
200.699996910.4%
 
171.600006110.4%
 
171.510.4%
 
168.699996910.4%
 
167.800003110.4%
 
163.899993910.4%
 
15810.4%
 
157.300003110.4%
 
154.199996910.4%
 
149.510.4%
 

col_8
Real number (ℝ≥0)

HIGH CORRELATION
ZEROS

Distinct count215
Unique (%)91.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean51.46553187677835
Minimum0.0
Maximum191.3999938964844
Zeros3
Zeros (%)1.3%
Memory size2.0 KiB
2020-08-25T00:59:43.568487image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1.490000033
Q116.29999971
median41.90000153
Q376.85000229
95-th percentile141.7099991
Maximum191.3999939
Range191.3999939
Interquartile range (IQR)60.55000257

Descriptive statistics

Standard deviation43.5278842
Coefficient of variation (CV)0.8457676936
Kurtosis0.2392923199
Mean51.46553188
Median Absolute Deviation (MAD)29.20000172
Skewness0.9401638737
Sum12094.39999
Variance1894.676703
2020-08-25T00:59:43.678897image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%) 
21.8999996231.3%
 
031.3%
 
9.30000019120.9%
 
66.9000015320.9%
 
3.520.9%
 
116.699996920.9%
 
52.2999992420.9%
 
520.9%
 
7820.9%
 
0.520.9%
 
8.60000038120.9%
 
5020.9%
 
22.2000007620.9%
 
70.1999969520.9%
 
3020.9%
 
56.7000007620.9%
 
3.09999990520.9%
 
120.9%
 
54.7000007610.4%
 
67.6999969510.4%
 
108.199996910.4%
 
39.0999984710.4%
 
2.09999990510.4%
 
37.5999984710.4%
 
0.100000001510.4%
 
Other values (190)19080.9%
 
ValueCountFrequency (%) 
031.3%
 
0.100000001510.4%
 
0.300000011910.4%
 
0.40000000610.4%
 
0.520.9%
 
0.699999988110.4%
 
0.899999976210.4%
 
120.9%
 
1.70000004810.4%
 
1.89999997610.4%
 
ValueCountFrequency (%) 
191.399993910.4%
 
187.199996910.4%
 
165.300003110.4%
 
162.800003110.4%
 
159.399993910.4%
 
157.899993910.4%
 
15310.4%
 
149.600006110.4%
 
145.100006110.4%
 
143.800003110.4%
 

col_9
Real number (ℝ≥0)

HIGH CORRELATION
ZEROS

Distinct count202
Unique (%)86.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean52.06510648644985
Minimum0.0
Maximum200.1999969482422
Zeros5
Zeros (%)2.1%
Memory size2.0 KiB
2020-08-25T00:59:43.801482image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1.469999993
Q116.55000019
median40.70000076
Q373.70000076
95-th percentile138.3899979
Maximum200.1999969
Range200.1999969
Interquartile range (IQR)57.15000057

Descriptive statistics

Standard deviation44.75650153
Coefficient of variation (CV)0.85962566
Kurtosis0.5248324911
Mean52.06510649
Median Absolute Deviation (MAD)28.00000095
Skewness1.025068565
Sum12235.30002
Variance2003.144429
2020-08-25T00:59:43.914391image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%) 
052.1%
 
0.20000000331.3%
 
431.3%
 
10320.9%
 
2.29999995220.9%
 
29.2999992420.9%
 
54.9000015320.9%
 
16.8999996220.9%
 
61.2999992420.9%
 
54.7999992420.9%
 
25.8999996220.9%
 
30.1000003820.9%
 
21.7999992420.9%
 
107.199996920.9%
 
8.89999961920.9%
 
61.5999984720.9%
 
33.2000007620.9%
 
8.39999961920.9%
 
39.7000007620.9%
 
5020.9%
 
38.7000007620.9%
 
48.0999984720.9%
 
11220.9%
 
12.6999998120.9%
 
6020.9%
 
Other values (177)18076.6%
 
ValueCountFrequency (%) 
052.1%
 
0.20000000331.3%
 
0.300000011910.4%
 
0.510.4%
 
110.4%
 
1.39999997610.4%
 
1.510.4%
 
2.09999990510.4%
 
2.29999995220.9%
 
2.79999995210.4%
 
ValueCountFrequency (%) 
200.199996910.4%
 
199.600006110.4%
 
188.800003110.4%
 
169.600006110.4%
 
158.699996910.4%
 
15810.4%
 
157.899993910.4%
 
154.510.4%
 
153.800003110.4%
 
142.199996910.4%
 

col_10
Real number (ℝ≥0)

HIGH CORRELATION
ZEROS

Distinct count200
Unique (%)85.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean52.28170197276359
Minimum0.0
Maximum235.8000030517578
Zeros5
Zeros (%)2.1%
Memory size2.0 KiB
2020-08-25T00:59:44.035659image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile2.960000062
Q114.5999999
median42.70000076
Q377
95-th percentile145.2299988
Maximum235.8000031
Range235.8000031
Interquartile range (IQR)62.4000001

Descriptive statistics

Standard deviation45.76395522
Coefficient of variation (CV)0.8753340746
Kurtosis1.182353324
Mean52.28170197
Median Absolute Deviation (MAD)30.89999771
Skewness1.164901779
Sum12286.19996
Variance2094.339597
2020-08-25T00:59:44.137148image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%) 
052.1%
 
431.3%
 
2.40000009531.3%
 
2420.9%
 
11.520.9%
 
33.520.9%
 
17.2000007620.9%
 
79.9000015320.9%
 
5.19999980920.9%
 
65.9000015320.9%
 
8.19999980920.9%
 
50.2000007620.9%
 
11.1000003820.9%
 
38.7999992420.9%
 
4.40000009520.9%
 
5.69999980920.9%
 
51.2999992420.9%
 
28.2000007620.9%
 
100.699996920.9%
 
13.520.9%
 
17.7999992420.9%
 
1620.9%
 
2820.9%
 
61.2999992420.9%
 
93.6999969520.9%
 
Other values (175)18076.6%
 
ValueCountFrequency (%) 
052.1%
 
0.40000000610.4%
 
0.600000023810.4%
 
1.20000004810.4%
 
1.510.4%
 
2.40000009531.3%
 
3.20000004810.4%
 
431.3%
 
4.19999980910.4%
 
4.30000019110.4%
 
ValueCountFrequency (%) 
235.800003110.4%
 
201.199996910.4%
 
188.399993910.4%
 
173.199996910.4%
 
171.699996910.4%
 
169.399993910.4%
 
167.300003110.4%
 
161.199996910.4%
 
157.300003110.4%
 
15510.4%
 

col_11
Real number (ℝ≥0)

HIGH CORRELATION
ZEROS

Distinct count207
Unique (%)88.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean51.86468073370609
Minimum0.0
Maximum253.8000030517578
Zeros3
Zeros (%)1.3%
Memory size2.0 KiB
2020-08-25T00:59:44.244523image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile3.840000081
Q116.59999943
median43.79999924
Q371.5
95-th percentile143.3199982
Maximum253.8000031
Range253.8000031
Interquartile range (IQR)54.90000057

Descriptive statistics

Standard deviation43.98236207
Coefficient of variation (CV)0.848021456
Kurtosis2.033520559
Mean51.86468073
Median Absolute Deviation (MAD)27.70000076
Skewness1.30738695
Sum12188.19997
Variance1934.448173
2020-08-25T00:59:44.347028image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%) 
14.3000001931.3%
 
57.2000007631.3%
 
031.3%
 
831.3%
 
75.520.9%
 
12.3000001920.9%
 
23.2000007620.9%
 
12.6999998120.9%
 
6.09999990520.9%
 
25.6000003820.9%
 
46.2999992420.9%
 
50.5999984720.9%
 
71.520.9%
 
8920.9%
 
34.4000015320.9%
 
8.19999980920.9%
 
28.520.9%
 
61.4000015320.9%
 
2.09999990520.9%
 
37.7000007620.9%
 
90.8000030520.9%
 
61.7000007620.9%
 
1420.9%
 
4.59999990520.9%
 
38.0999984710.4%
 
Other values (182)18277.4%
 
ValueCountFrequency (%) 
031.3%
 
0.40000000610.4%
 
1.10000002410.4%
 
1.510.4%
 
2.09999990520.9%
 
2.59999990510.4%
 
310.4%
 
3.09999990510.4%
 
3.70000004810.4%
 
3.90000009510.4%
 
ValueCountFrequency (%) 
253.800003110.4%
 
186.199996910.4%
 
181.510.4%
 
180.399993910.4%
 
164.699996910.4%
 
163.600006110.4%
 
162.399993910.4%
 
158.199996910.4%
 
15710.4%
 
156.300003110.4%
 

col_12
Real number (ℝ≥0)

HIGH CORRELATION
ZEROS

Distinct count209
Unique (%)88.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean50.64170205497995
Minimum0.0
Maximum210.8999938964844
Zeros5
Zeros (%)2.1%
Memory size2.0 KiB
2020-08-25T00:59:44.459956image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile2.29999994
Q114.75
median40.5
Q368.45000076
95-th percentile139.6799957
Maximum210.8999939
Range210.8999939
Interquartile range (IQR)53.70000076

Descriptive statistics

Standard deviation43.13203793
Coefficient of variation (CV)0.8517098791
Kurtosis0.9163807734
Mean50.64170205
Median Absolute Deviation (MAD)26.69999695
Skewness1.101421799
Sum11900.79998
Variance1860.372696
2020-08-25T00:59:44.559683image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%) 
052.1%
 
54.7999992431.3%
 
2531.3%
 
33.2999992420.9%
 
8.39999961920.9%
 
10.6999998120.9%
 
54.2999992420.9%
 
28.8999996220.9%
 
17.7000007620.9%
 
3820.9%
 
30.7000007620.9%
 
7.90000009520.9%
 
77.4000015320.9%
 
14.520.9%
 
10.520.9%
 
5720.9%
 
99.6999969520.9%
 
7.40000009520.9%
 
1720.9%
 
6720.9%
 
97.9000015320.9%
 
115.400001510.4%
 
2.59999990510.4%
 
74.4000015310.4%
 
50.9000015310.4%
 
Other values (184)18478.3%
 
ValueCountFrequency (%) 
052.1%
 
0.20000000310.4%
 
0.300000011910.4%
 
0.600000023810.4%
 
0.699999988110.4%
 
0.800000011910.4%
 
1.10000002410.4%
 
1.60000002410.4%
 
2.59999990510.4%
 
2.70000004810.4%
 
ValueCountFrequency (%) 
210.899993910.4%
 
201.300003110.4%
 
183.300003110.4%
 
158.600006110.4%
 
152.300003110.4%
 
150.300003110.4%
 
148.100006110.4%
 
147.899993910.4%
 
147.510.4%
 
14610.4%
 

target
Real number (ℝ≥0)

HIGH CORRELATION
ZEROS

Distinct count211
Unique (%)89.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean51.51446809844768
Minimum0.0
Maximum239.3999938964844
Zeros6
Zeros (%)2.6%
Memory size2.0 KiB
2020-08-25T00:59:44.665181image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1.380000007
Q117.25
median41.20000076
Q374.70000076
95-th percentile131.65
Maximum239.3999939
Range239.3999939
Interquartile range (IQR)57.45000076

Descriptive statistics

Standard deviation45.06595793
Coefficient of variation (CV)0.8748213772
Kurtosis1.734200182
Mean51.5144681
Median Absolute Deviation (MAD)26.89999771
Skewness1.296485066
Sum12105.9
Variance2030.940564
2020-08-25T00:59:44.767648image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%) 
062.6%
 
4031.3%
 
6031.3%
 
6.69999980931.3%
 
9.89999961931.3%
 
28.3999996220.9%
 
1.10000002420.9%
 
0.300000011920.9%
 
7.80000019120.9%
 
25.7999992420.9%
 
47.2999992420.9%
 
29.8999996220.9%
 
10.520.9%
 
34.520.9%
 
7.19999980920.9%
 
43.2000007620.9%
 
46.0999984710.4%
 
70.4000015310.4%
 
159.899993910.4%
 
112.699996910.4%
 
45.2000007610.4%
 
83.510.4%
 
95.6999969510.4%
 
25.7000007610.4%
 
192.100006110.4%
 
Other values (186)18679.1%
 
ValueCountFrequency (%) 
062.6%
 
0.300000011920.9%
 
0.510.4%
 
0.800000011910.4%
 
1.10000002420.9%
 
1.510.4%
 
2.20000004810.4%
 
2.29999995210.4%
 
2.510.4%
 
2.79999995210.4%
 
ValueCountFrequency (%) 
239.399993910.4%
 
206.199996910.4%
 
192.100006110.4%
 
187.600006110.4%
 
176.300003110.4%
 
174.399993910.4%
 
17410.4%
 
159.899993910.4%
 
157.300003110.4%
 
150.100006110.4%
 

Interactions

2020-08-25T00:59:19.018593image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:59:19.128619image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:59:19.234464image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:59:19.351688image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:59:19.475301image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:59:19.598280image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:59:19.711104image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:59:19.834695image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:59:20.126421image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:59:20.252774image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:59:20.375058image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:59:20.498924image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:59:20.611868image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:59:20.726048image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:59:20.836175image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:59:20.960121image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:59:21.082680image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:59:21.210926image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:59:21.338726image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:59:21.450529image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:59:21.576992image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:59:21.702319image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:59:21.831785image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:59:21.937426image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:59:22.047112image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:59:22.154359image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:59:22.264064image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:59:22.387988image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:59:22.516313image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:59:22.655762image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:59:22.796903image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:59:22.933721image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:59:23.060988image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:59:23.210310image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:59:23.349560image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:59:23.495156image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:59:23.623032image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:59:23.757286image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:59:24.059200image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:59:24.186381image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:59:24.312541image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:59:24.436610image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:59:24.574077image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:59:24.714457image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:59:24.864564image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:59:24.994625image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:59:25.140943image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:59:25.284555image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:59:25.425848image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:59:25.557229image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:59:25.693851image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:59:25.822848image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:59:25.953935image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:59:26.082129image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:59:26.213027image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:59:26.349918image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:59:26.490188image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:59:26.632738image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:59:26.764570image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:59:26.902068image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:59:27.042288image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:59:27.186656image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:59:27.323434image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:59:27.458446image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:59:27.584728image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:59:27.719053image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:59:28.009011image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:59:28.126326image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:59:28.254286image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:59:28.387794image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:59:28.518384image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:59:28.636235image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:59:28.768153image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:59:28.895169image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:59:29.028541image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:59:29.139248image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:59:29.265700image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:59:29.383847image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:59:29.500678image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:59:29.629916image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:59:29.761205image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:59:29.900246image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:59:30.042014image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:59:30.185960image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:59:30.315246image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:59:30.454136image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:59:30.596096image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:59:30.743821image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:59:30.870067image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:59:30.997457image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:59:31.122005image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:59:31.256557image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:59:31.383618image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:59:31.506986image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:59:31.645187image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:59:31.961636image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:59:32.103190image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:59:32.236885image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:59:32.375906image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:59:32.520856image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:59:32.665045image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:59:32.794296image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:59:32.925744image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:59:33.057091image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:59:33.191316image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:59:33.323008image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:59:33.448294image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:59:33.583605image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:59:33.721123image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:59:33.871032image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:59:33.998253image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:59:34.135516image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:59:34.274904image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:59:34.413336image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:59:34.547675image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:59:34.683041image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:59:34.809714image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:59:34.935620image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:59:35.043426image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:59:35.148848image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:59:35.269397image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:59:35.388303image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:59:35.506204image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:59:35.613770image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:59:35.909164image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:59:36.034446image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:59:36.158986image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:59:36.264972image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:59:36.373245image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:59:36.481072image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:59:36.586848image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:59:36.697481image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:59:36.808622image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:59:36.928396image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:59:37.054922image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:59:37.175895image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:59:37.291423image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:59:37.419580image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:59:37.541832image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:59:37.665211image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:59:37.774007image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:59:37.890072image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:59:38.000801image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:59:38.119237image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:59:38.227988image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:59:38.335716image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:59:38.454481image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:59:38.577605image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:59:38.698495image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:59:38.806898image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:59:38.928373image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:59:39.044871image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:59:39.163272image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:59:39.266093image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:59:39.376541image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:59:39.657742image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:59:39.766163image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:59:39.883694image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:59:40.000266image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:59:40.121668image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:59:40.245112image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:59:40.370682image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:59:40.487972image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:59:40.611479image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:59:40.737082image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:59:40.859905image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:59:40.973240image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:59:41.092263image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:59:41.203740image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/

Correlations

2020-08-25T00:59:44.895016image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/

Pearson's r

The Pearson's correlation coefficient (r) is a measure of linear correlation between two variables. It's value lies between -1 and +1, -1 indicating total negative linear correlation, 0 indicating no linear correlation and 1 indicating total positive linear correlation. Furthermore, r is invariant under separate changes in location and scale of the two variables, implying that for a linear function the angle to the x-axis does not affect r.

To calculate r for two variables X and Y, one divides the covariance of X and Y by the product of their standard deviations.
2020-08-25T00:59:45.134257image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/

Spearman's ρ

The Spearman's rank correlation coefficient (ρ) is a measure of monotonic correlation between two variables, and is therefore better in catching nonlinear monotonic correlations than Pearson's r. It's value lies between -1 and +1, -1 indicating total negative monotonic correlation, 0 indicating no monotonic correlation and 1 indicating total positive monotonic correlation.

To calculate ρ for two variables X and Y, one divides the covariance of the rank variables of X and Y by the product of their standard deviations.
2020-08-25T00:59:45.368389image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/

Kendall's τ

Similarly to Spearman's rank correlation coefficient, the Kendall rank correlation coefficient (τ) measures ordinal association between two variables. It's value lies between -1 and +1, -1 indicating total negative correlation, 0 indicating no correlation and 1 indicating total positive correlation.

To calculate τ for two variables X and Y, one determines the number of concordant and discordant pairs of observations. τ is given by the number of concordant pairs minus the discordant pairs divided by the total number of pairs.
2020-08-25T00:59:45.604553image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/

Phik (φk)

Phik (φk) is a new and practical correlation coefficient that works consistently between categorical, ordinal and interval variables, captures non-linear dependency and reverts to the Pearson correlation coefficient in case of a bivariate normal input distribution. There is extensive documentation available here.

Missing values

2020-08-25T00:59:41.437422image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/
2020-08-25T00:59:41.733386image/svg+xmlMatplotlib v3.3.1, https://matplotlib.org/

Sample

First rows

col_1col_2col_3col_4col_5col_6col_7col_8col_9col_10col_11col_12target
01749.058.00000062.59999870.00000055.70000185.00000083.50000094.80000366.30000375.90000275.500000158.60000685.199997
11750.073.30000375.90000289.19999788.30000390.000000100.00000085.400002103.00000091.19999765.69999763.29999975.400002
21751.070.00000043.50000045.29999956.40000260.70000150.70000166.30000359.79999923.50000023.20000128.50000044.000000
31752.035.00000050.00000071.00000059.29999959.70000139.59999878.40000229.29999927.10000046.59999837.59999840.000000
41753.044.00000032.00000045.70000138.00000036.00000031.70000122.20000139.00000028.00000025.00000020.0000006.700000
51754.00.0000003.0000001.70000013.70000020.70000126.70000118.79999912.3000008.20000024.10000013.2000004.200000
61755.010.20000011.2000006.8000006.5000000.0000000.0000008.6000003.20000017.79999923.7000016.80000020.000000
71756.012.5000007.1000005.4000009.40000012.50000012.9000003.6000006.40000011.80000014.30000017.0000009.400000
81757.014.10000021.20000126.20000130.00000038.09999812.80000025.00000051.29999939.70000132.50000064.69999733.500000
91758.037.59999852.00000049.00000072.30000346.40000245.00000044.00000038.70000162.50000037.70000143.00000043.000000

Last rows

col_1col_2col_3col_4col_5col_6col_7col_8col_9col_10col_11col_12target
2251974.027.60000026.00000021.29999940.29999939.50000036.00000055.79999933.59999840.20000147.09999825.00000020.500000
2261975.018.90000011.50000011.5000005.1000009.00000011.40000028.20000139.70000113.9000009.10000019.4000007.800000
2271976.08.1000004.30000021.90000018.79999912.40000012.2000001.90000016.40000013.50000020.6000005.20000015.300000
2281977.016.40000023.1000008.70000012.90000018.60000038.50000021.40000030.10000044.00000043.79999929.10000043.200001
2291978.051.90000293.59999876.50000099.69999782.69999795.09999870.40000258.099998138.199997125.09999897.900002122.699997
2301979.0166.600006137.500000138.000000101.500000134.399994149.500000159.399994142.199997188.399994186.199997183.300003176.300003
2311980.0159.600006155.000000126.199997164.100006179.899994157.300003136.300003135.399994155.000000164.699997147.899994174.399994
2321981.0114.000000141.300003135.500000156.399994127.50000090.000000143.800003158.699997167.300003162.399994137.500000150.100006
2331982.0111.199997163.600006153.800003122.00000082.199997110.400002106.099998107.599998118.80000394.69999798.099998127.000000
2341983.084.30000351.00000066.50000080.69999799.19999791.09999882.19999771.80000350.29999955.79999933.29999933.400002